Vector Analysis Based Multiobjective-Modulated Model Predictive Control for Four-Switching-State Multilevel Converters

Abstract

The article proposes a new vector analysis based model predictive control (VAMPC) method for multilevel converters with four different switch configurations. It is based on track of an error vector using fundamental state vectors, and can achieve deadbeat control of four switching states multilevel converters with multiple control objectives. Compared with conventional finite control set model predictive control (FCS-MPC) method, VAMPC can achieve excellent spectrum characteristics in the case of a slight increase in computational burden. The VAMPC method is experimentally validated on a 100-kHz GaN-based three-level flying capacitor (FC) converter. Compared with the FCS-MPC, VAMPC leads to significant reduction in steady-state control errors. For example, the inductor current total harmonic distortion of the FC converter is now reduced by more than 60%.